Senior Data Scientist - Content

Your Mission

Establishing and maintaining high-quality data infrastructure, data assets, and data science capabilities are critical for the company's continued success. We have and will continue to invest heavily to leverage data science and machine learning to drive strategic and business decisions, power key product features, and solve problems that directly improve our customers’ experience and the strength of our business. As a Data Scientist at Engine, you’ll play a vital role in an environment where innovation meets collaboration. Here’s what you’ll take charge of:

• Develop and implement data science strategies to enhance key machine learning models and services, including lead scoring, churn modeling, pricing, personalization, and fraud detection.
• Collaborate with engineering and business stakeholders to ensure actionable insights, effective implementation, and measurable business impact.
• Drive end-to-end data science initiatives, from gathering and analyzing data to feature engineering, model selection/training, inference, and monitoring.
• Enhance data infrastructure and analytics capabilities by working closely with our data infrastructure and analyst teams.
• Effectively communicate findings to both technical and non-technical audiences, ensuring transparency and alignment across teams.

What You’ll Bring to Engine

We’re looking for someone who’s ready to make an impact and grow alongside us:

• Experience: 5+ years of industry experience as a Data Scientist/ML Engineer in high-growth environments.
• Technical Skills: Strong expertise in machine learning algorithms and statistical modeling, with proficiency in Python (including scikit-learn, numpy, and pandas) and SQL. Experience with Snowflake and Streamlit is a plus.
• Education: MS/PhD in a quantitative discipline such as Mathematics, Statistics, Operations Research, Economics, Engineering, or Computer Science.
• Problem-Solving Mindset: A bias toward simple, effective ML solutions before diving into complex approaches.
• Communication Skills: Ability to present findings clearly to both technical and non-technical stakeholders.
• Adaptability: Thrive in a fast-paced, dynamic environment with a willingness to take initiative and drive meaningful impact.